Generative Adversarial Networks (GANs) are a deep learning architecture used for generative tasks, such as image generation, style transfer, and text-to-image synthesis. They consist of two neural networks: a generator and a discriminator. The generator creates new data samples while the discriminator evaluates them, trying to distinguish real data from generated ones. During training, the … Continue reading Advancement in Generative Adversarial Networks (GANs) for Image Generation: A Step Towards Sign Language Production